"Traditional Welsh Dish Cawl" matching MCP servers:

Provides traditional Chinese metaphysics analysis capabilities including I Ching divination (hexagram generation and interpretation) and Bazi (Four Pillars) fortune-telling with comprehensive life analysis covering career, wealth, relationships, and health predictions.

Bridges TiMEM's cloud MCP server with DeepSeek Harness to provide long-term memory tools and automatic memory skills for AI models, enabling persistent context and learned behaviors across conversations.

Enables DeepSeek Harness agents to access DeepBrain's judgment store, including quoting verified lines, retrieving historical positions, and reusing analysis methods.

An open-source MCP server for RAG over personal documents. Supports three parallel strategies — Traditional, Contextual, and Graph RAG — with all data stored locally for privacy.

Enables structural knowledge-graph code search, AST snippet retrieval, architecture analysis, call-path tracing, and textual code search across indexed repositories, plus an auto-started graph visualization UI.

Search and read locally-recorded meeting transcripts over stdio. Read-only, no network. Exposes list_sessions, get_session, and search_transcripts to any MCP client.

MCP server for verifying narrative consistency and querying story-state facts in DeepSeek Harness, exposing read-only ledger tools for canonical evidence and continuity checks.

Preserve grandma's handwritten recipe cards before they're lost. 13 MCP tools to OCR-import cards from photos, capture the story behind each dish (who made it, when, why), search by family member, plan meals, and share with cousins — backed by a real cookbook app that prints as a hardcover heirloom. Free tier, no credit card.

Exposes DeepSeek Harness capabilities—durable memory, task ledger, project-agent dispatch, and the wider MCP estate—as declared MCP tools for any MCP client.

Provides a cross-session experience knowledge base for AI agents, enabling retrieval of past problem-solution experiences via MCP tools. It helps agents reuse solutions without retraining, with zero-LLM runtime retrieval.

Enables DeepSeek Harness to use OpenViking persistent memory by recalling relevant context into conversations, mirroring sessions, committing at thresholds, replaying offline writes, and exposing OpenViking tools via MCP while guarding viking:// URIs.

A graph-based MCP server that provides AI coding agents with persistent memory to store patterns, track complex relationships, and retrieve knowledge across sessions. It leverages graph structures to handle temporal queries and relational paths that traditional vector stores often miss.

Enables creation of persistent, compounding knowledge bases using Karpathy's LLM Wiki pattern with LLM-maintained markdown wikis. Supports automated ingestion, cross-referencing, synthesis, and linting of sources as an alternative to traditional RAG systems.

Korean traditional saju (four pillars) fortune analysis MCP server with a premium web GUI dashboard for local data persistence, 100-point scoring, and history management.

Enables enterprise knowledge search through a chat interface, comparing traditional RAG with MCP-driven retrieval using hybrid BM25 and dense vector search, Ollama-powered answer generation, and question routing to domain-specific retrieval tools.

Recommends dishes from a global cuisine knowledge base based on user preferences (keywords, cuisine, price, etc.) via weighted random selection with bias correction and diversity.

MCP server exposing memory search, index, and stats tools for agents, with honesty guards to prevent re-litigation of settled decisions.

Compresses AI chat sessions into a typed knowledge graph (~300–800 tokens). Works file-based in Copilot, Claude Code, Cursor, and Gemini CLI without MCP server mode. Supports local/offline extraction via Ollama — no API key required.

Enables AI assistants to search, retrieve, and browse Markdown documentation in a local folder, then answer questions with cited sources.

Provides persistent OKF memory for DeepSeek Harness by storing and indexing Markdown memories in SQLite FTS5, enabling agents to search, store, and export memories through MCP tools.